# # flake8: noqa
# # There's no way to ignore "F401 '...' imported but unused" warnings in this
# # module, but to preserve other warnings. So, don't check this module at all.
#
# # Copyright 2020 The HuggingFace Team. All rights reserved.
# #
# # Licensed under the Apache License, Version 2.0 (the "License");
# # you may not use this file except in compliance with the License.
# # You may obtain a copy of the License at
# #
# #     http://www.apache.org/licenses/LICENSE-2.0
# #
# # Unless required by applicable law or agreed to in writing, software
# # distributed under the License is distributed on an "AS IS" BASIS,
# # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# # See the License for the specific language governing permissions and
# # limitations under the License.
#
# from typing import TYPE_CHECKING
#
# from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
#
#
# _import_structure = {
#     "configuration_deberta": ["DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DebertaConfig"],
#     "tokenization_deberta": ["DebertaTokenizer"],
# }
#
# if is_tokenizers_available():
#     _import_structure["tokenization_deberta_fast"] = ["DebertaTokenizerFast"]
#
# if is_torch_available():
#     _import_structure["modeling_deberta"] = [
#         "DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST",
#         "DebertaForMaskedLM",
#         "DebertaForQuestionAnswering",
#         "DebertaForSequenceClassification",
#         "DebertaForTokenClassification",
#         "DebertaModel",
#         "DebertaPreTrainedModel",
#     ]
#
#
# if TYPE_CHECKING:
#     from .configuration_deberta import DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, DebertaConfig
#     from .tokenization_deberta import DebertaTokenizer
#
#     if is_tokenizers_available():
#         from .tokenization_deberta_fast import DebertaTokenizerFast
#
#     if is_torch_available():
#         from .modeling_deberta import (
#             DEBERTA_PRETRAINED_MODEL_ARCHIVE_LIST,
#             DebertaForMaskedLM,
#             DebertaForQuestionAnswering,
#             DebertaForSequenceClassification,
#             DebertaForTokenClassification,
#             DebertaModel,
#             DebertaPreTrainedModel,
#         )
#
# else:
#     import sys
#
#     sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)
